摘要
目的基于网络药理学研究冬凌草抗癌的活性成分及作用机制。方法通过人类孟德尔遗传数据库(OMIM)及基因疾病关联数据库(DisGeNET)筛选出与癌症相关的疾病靶点,并经过Uniprot数据库对靶点基因进行标准化;通过BATMAN-TCM数据库、TCM-ID数据库、中国天然产物化学成分库并结合文献查找出冬凌草的成分,同时将这些成分按照类药五原则(Lipinski规则)筛选出有效成分,再通过PubChem数据库,Chemmapper数据库,PharmMapper数据库和Swiss Target Prediction等数据库收集冬凌草靶点并经过Uniprot数据库标准化;采用String数据库构建冬凌草治疗癌症的靶点相互作用的网络。通过Cytoscape 3.7.1软件绘制关系图并进行网络拓扑参数分析,并利用DAVID 6.8数据库进行基因本体论(GO)分析和京都基因与基因组百科全书(KEGG)通路分析;最后通过imageGP工具绘制GO和KEGG气泡图。结果筛选出30个冬凌草抗癌有效成分及对应靶点265个,最终得到与癌症相关靶点5个及活性成分22个,冬凌草中重要的抗癌成分分别是α-柠檬烯、β-蒎烯、D-柠檬烯及甲基异茜草素,且是通过调控雌激素受体1(ESR1)、雄激素受体(AR)、白细胞介素1β(IL1B)、羟基类固醇17-β脱氢酶1(HSD17B1)等关键疾病靶点起到抗癌的效果,并通过参与癌症通路、癌症蛋白聚糖通路、细胞丝裂原活化蛋白激酶(MAPK)信号通路、磷脂酰肌醇3激酶(PI3K)/AKT(蛋白激酶B)信号通路、前列腺癌、FoxO转录因子信号通路、癌症微小核糖核酸表达、非酒精性脂肪肝(NAFLD)等通路发挥抗癌作用。结论冬凌草中多种化学成分可以从多个靶点、多条途径治疗癌症,为清热解毒药物在治疗癌症的作用机制提供理论支持。
Objective To explore the activity components and mechanism of Donglingcao (Rabdosiae Rubescentis Herba) in anti-cancer treatment by using network pharmacology. Methods Disease targets for cancer were collected through databases of gene-disease associations (DisGeNET) and Online Mendelian Inheritance in Man (OMIM). Then target genes were standardized through the Uniprot database. The components of Donglingcao (Rabdosiae Rubescentis Herba) were fount out by searching BATMAN-TCM database, TCM-ID database and the database of chemical composition of natural products in China and relevant literature. At the same time, these components were screened out according to the five principles of the drug (Lipinski rule). After that, the target of Donglingcao (Rabdosiae Rubescentis Herba) was collected through the PubChem database, Chemmapper database, PharmMapper database and Swiss Target Prediction database and standardized by the Uniprot database. String database was used to construct a network of target interactions for the treatment of tumor by Donglingcao (Rabdosiae Rubescentis Herba). A network topology was drawn and analyzed through Cytoscape 3.7.1 software, and DAVID 6.8 database was used for gene ontology (GO) analysis and Kyoto Genomics and Genomics Encyclopedia (KEGG) pathway analysis. Finally GO and KEGG bubbles figure was drawn by imageGP tool. Results A total of 265 anti-cancer active ingredients and corresponding targets were screened out, and 51 cancer-related targets and 22 active components were obtained. The important anti-tumor components in Donglingcao (Rabdosiae Rubescentis Herba) were α-pinene, β-pinene, D-Limonene and Rubiadin, meanwhile played an anti-cancer effect by regulating estrogen receptor 1 (ESR1), androgen receptor (AR), interleukin 1β (IL1 B), hydroxysteroid 17-β dehydrogenase key disease targets (HSD17 B1) and participating in the cancer pathway, the proteoglycan pathway, the mitogen-activated protein kinase (MAPK) signaling pathway and phosphatidylinositol 3-kinase (PI3 K)/AKT (protein kinase B) signaling pathway, prostate cancer, FoxO transcription factor signaling pathway, cancer microRNA expression, non-alcoholic fatty liver (NAFLD) and other pathways. Conclusion A variety of chemical constituents in Donglingcao (Rabdosiae Rubescentis Herba) can treat cancer from multiple targets and multiple pathways, providing theoretical support for the mechanism of heat-clearing and detoxifying drugs treating cancer.
作者
欧阳思露
杨柱
龙奉玺
罗莉
吴群
杨静
唐东昕
OUYANG Silu;YANG Zhu;LONG Fengxi;LUO Li;WU Qun;YANG Jing;TANG Dongxin(Tumor Inheritance and Scientific and Technological Innovation Talents Base of Traditional Chinese Medicine in Guizhou Province,Guizhou University of Traditional Chinese Medicine,Guiyang 550002,Guizhou,China)
出处
《中华中医药学刊》
CAS
北大核心
2021年第4期192-195,I0058,I0059,共6页
Chinese Archives of Traditional Chinese Medicine
基金
贵州省科技厅项目(黔科合人才[2016]4032)
贵州省组织部项目(黔人颁发[2018]3)
贵州省中医药管理局项目(黔财社[2016]117)
贵州省研究生工作站计划(黔教研合JYSZ字[2014]018)。
关键词
冬凌草
网络药理学
癌症
靶点预测
Donglingcao(Rabdosiae Rubescentis Herba)
network pharmacology
cancer
targets prediction
